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Decoding Method Based on Complex ICA for a Multicell Massive MIMO Uplink System
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DOI：10.1109/LSP.2016.2545105.png)
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摘要
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Pilot signal reuse in neighboring cells causes the pilot contamination, and performance will be degraded significantly in a multicell, massive multiple-input, multiple-output (MIMO) uplink system. In this letter, a new decoding method is proposed to alleviate the degradation. In the proposed method, the principal component analysis (PCA) is used to reduce the dimension of the received signals from both intercell and intracell. Then, the complex independent component analysis (ICA) is implemented to estimate the channels, and the mean minimum square error (MMSE) decoder is employed to decode the transmitted signals. At last, few pilot signals are used to overcome the ambiguity caused by the complex ICA. In our method, orthogonality or asymptotic orthogonality of the channels is not required. Moreover, the path-loss and shadowing factors can be unknown. Simulation results show that the performance of our decoder is better than the MMSE channel estimation-based MMSE decoder. Moreover, error floor does not appear even when signal-to-noise ratio (SNR) is high, while it occurs if the MMSE decoder is used.
Keyword:
Independent component analysis (ICA)
multicell massive multiple-input
multiple-output (MIMO) system
pilot contamination
pilot signals
principal component analysis (PCA)
semi-blind decoding
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9.6
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1.1W
被引数:
1.7W
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